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Title: The MC21 Monte Carlo Transport Code

Abstract

MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities.

Authors:
Publication Date:
Research Org.:
Knolls Atomic Power Laboratory (KAPL), Niskayuna, NY
Sponsoring Org.:
USDOE
OSTI Identifier:
903083
Report Number(s):
LM-06K144
TRN: US0703198
DOE Contract Number:
DE-AC12-00SN39357
Resource Type:
Conference
Resource Relation:
Conference: Joint International Topical Meeting on Mathematics and Computation and Supercomputing in Nuclear Applications, Monterey, CA, April 15 -19, 2007
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; BETTIS; DESIGN; GEOMETRY; KAPL; KERNELS; MONTE CARLO METHOD; NEUTRONS; PHOTON TRANSPORT; PHYSICS; SIMULATION; TRANSPORT; VISION

Citation Formats

Sutton TM, Donovan TJ, Trumbull TH, Dobreff PS, Caro E, Griesheimer DP, Tyburski LJ, Carpenter DC, Joo H. The MC21 Monte Carlo Transport Code. United States: N. p., 2007. Web.
Sutton TM, Donovan TJ, Trumbull TH, Dobreff PS, Caro E, Griesheimer DP, Tyburski LJ, Carpenter DC, Joo H. The MC21 Monte Carlo Transport Code. United States.
Sutton TM, Donovan TJ, Trumbull TH, Dobreff PS, Caro E, Griesheimer DP, Tyburski LJ, Carpenter DC, Joo H. Tue . "The MC21 Monte Carlo Transport Code". United States. doi:. https://www.osti.gov/servlets/purl/903083.
@article{osti_903083,
title = {The MC21 Monte Carlo Transport Code},
author = {Sutton TM, Donovan TJ, Trumbull TH, Dobreff PS, Caro E, Griesheimer DP, Tyburski LJ, Carpenter DC, Joo H},
abstractNote = {MC21 is a new Monte Carlo neutron and photon transport code currently under joint development at the Knolls Atomic Power Laboratory and the Bettis Atomic Power Laboratory. MC21 is the Monte Carlo transport kernel of the broader Common Monte Carlo Design Tool (CMCDT), which is also currently under development. The vision for CMCDT is to provide an automated, computer-aided modeling and post-processing environment integrated with a Monte Carlo solver that is optimized for reactor analysis. CMCDT represents a strategy to push the Monte Carlo method beyond its traditional role as a benchmarking tool or ''tool of last resort'' and into a dominant design role. This paper describes various aspects of the code, including the neutron physics and nuclear data treatments, the geometry representation, and the tally and depletion capabilities.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 09 00:00:00 EST 2007},
month = {Tue Jan 09 00:00:00 EST 2007}
}

Conference:
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  • The geometry kernel of the developmental Monte Carlo transport code MC21 is designed as a combination of the geometry capabilities of several existing Monte Carlo codes. This combination of capabilities is intended to meet efficiently the general requirements associated with in-core design products and, at the same time, be flexible enough to support highly general geometric models. This paper provides a description of the different geometry representations of MC21 and outlines how the geometric data is stored internally through the use of Fortran-90 data structures. Finally, two alternative geometric representations of a published BWR unit assembly model are discussed. Resultsmore » for the two representations are contrasted, including k-effective results, relative memory footprints, and relative computational speeds. While total memory footprint is not noticeably reduced, results show significant speed advantages of one representation. (authors)« less
  • With the recent emphasis in performing multiphysics calculations using Monte Carlo transport codes such as MC21, the need for accurate estimates of the energy deposition-and the subsequent heating - has increased. However, the availability and quality of data necessary to enable accurate neutron and photon energy deposition calculations can be an issue. A comprehensive method for handling the nuclear data required for energy deposition calculations in MC21 has been developed using the NDEX nuclear data processing system and leveraging the capabilities of NJOY. The method provides a collection of data to the MC21 Monte Carlo code supporting the computation ofmore » a wide variety of energy release and deposition tallies while also allowing calculations with different levels of fidelity to be performed. Detailed discussions on the usage of the various components of the energy release data are provided to demonstrate novel methods in borrowing photon production data, correcting for negative energy release quantities, and adjusting Q values when necessary to preserve energy balance. Since energy deposition within a reactor is a result of both neutron and photon interactions with materials, a discussion on the photon energy deposition data processing is also provided. (authors)« less
  • A description of a robust and flexible movable geometry implementation in the Monte Carlo code MC21 is described along with a search algorithm that can be used in conjunction with the movable geometry capability to perform eigenvalue searches based on the position of some geometric component. The natural use of the combined movement and search capability is searching to critical through variation of control rod (or control drum) position. The movable geometry discussion provides the mathematical framework for moving surfaces in the MC21 combinatorial solid geometry description. A discussion of the interface between the movable geometry system and the usermore » is also described, particularly the ability to create a hierarchy of movable groups. Combined with the hierarchical geometry description in MC21 the movable group framework provides a very powerful system for inline geometry modification. The eigenvalue search algorithm implemented in MC21 is also described. The foundations of this algorithm are a regula falsi search though several considerations are made in an effort to increase the efficiency of the algorithm for use with Monte Carlo. Specifically, criteria are developed to determine after each batch whether the Monte Carlo calculation should be continued, the search iteration can be rejected, or the search iteration has converged. These criteria seek to minimize the amount of time spent per iteration. Results for the regula falsi method are shown, illustrating that the method as implemented is indeed convergent and that the optimizations made ultimately reduce the total computational expense. (authors)« less
  • Due to the steadily decreasing cost and wider availability of large scale computing platforms, there is growing interest in the prospects for the use of Monte Carlo for reactor design calculations that are currently performed using few-group diffusion theory or other low-order methods. To facilitate the monitoring of the progress being made toward the goal of practical full-core reactor design calculations using Monte Carlo, a performance benchmark has been developed and made available through the Nuclear Energy Agency. A first analysis of this benchmark using the MC21 Monte Carlo code was reported on in 2010, and several practical difficulties weremore » highlighted. In this paper, a newer version of MC21 that addresses some of these difficulties has been applied to the benchmark. In particular, the confidence-interval-determination method has been improved to eliminate source correlation bias, and a fission-source-weighting method has been implemented to provide a more uniform distribution of statistical uncertainties. In addition, the Forward-Weighted, Consistent-Adjoint-Driven Importance Sampling methodology has been applied to the benchmark problem. Results of several analyses using these methods are presented, as well as results from a very large calculation with statistical uncertainties that approach what is needed for design applications. (authors)« less